Strategic Engineering

Motivation

Modern infrastructure networks—electricity, transport, and water—are increasingly interdependent. Disruptions in one system propagate through others, amplifying societal and economic losses. Traditional deterministic investment planning fails to capture the cascading effects of such interdependencies and the uncertainty of extreme events.
This study was motivated by the need for strategically flexible, risk-aware investment frameworks that can adapt to emerging hazards and changing urban dynamics. By embedding real options thinking into multi-stage infrastructure design, the researchers aimed to create a decision-support tool that values flexibility, enabling planners to defer, expand, or accelerate investments as uncertainty unfolds .

Methodologies

• System Modelling and Interdependency Representation: Built a network-of-networks model linking energy, water, and transport systems through spatial and functional dependencies. Infrastructure performance under disruption was modelled using a probabilistic failure and recovery simulation (Fig. 1–2, p. 283–284).
• Real Options-Based Multi-Stage Investment Framework: Investment decisions are structured as sequential options—e.g., the right but not obligation to expand or reinforce system nodes. This approach enables adaptive responses to future uncertainty.
• Mixed Integer Linear Programming (MILP) Optimisation: The MILP model determines optimal investment sequencing, subject to interdependency and budget constraints. Uncertainty is incorporated via scenario trees representing hazard intensities and system states.
• Monte Carlo Simulation and Bayesian Updating: Used to generate probabilistic demand and disruption scenarios; Bayesian updating refines beliefs about hazard frequencies as new information becomes available.
• Performance Metrics: Evaluated Expected Net Present Value (ENPV), Expected Loss Reduction (ELR), and System Recovery Time (SRT) across 1,000 Monte Carlo realisations (see Fig. 4–6, p. 286–288).

Insights

• Economic and Resilience Gains: The real-options strategy increased ENPV by 18 % compared with a static single-stage investment plan, while reducing expected disruption losses by 35 %. Recovery times across coupled systems improved by an average of 22 %, illustrating the benefit of flexibility in post-disaster recovery.
• Risk-Informed Staging: Early investment in key interdependent nodes (e.g., power substations supporting water pumps) provides outsized benefits under uncertain hazard intensities. Deferred investments allow adaptation to realised conditions.
• Strategic Implications: The research demonstrates that flexibility adds measurable economic value and robustness. It also supports cross-sector coordination, ensuring that limited budgets achieve the greatest risk-reduction effect.

Training

Relevant lectures and skills:

• Real Options Analysis
• Monte Carlo and Bayesian Modelling of Uncertainty
• Multi-Stage Investment Optimisation (MILP)
• Resilience Metrics and Interdependency Analysis
• Decision-Making

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